More Like this

1. Coexistence Between Wi-Fi and LTE on Unlicensed Spectrum: A Human-Centric Approach

   https://doi.org/10.1109/JSAC.2017.2680819  

   Yuan, Xu ; Qin, Xiaoqi ; Tian, Feng ; Hou, Y. Thomas ; Lou, Wenjing ; Midkiff, Scott F. ; Reed, Jeffrey H. ( April 2017 , IEEE Journal on Selected Areas in Communications)
2. CiFi: Deep convolutional neural networks for indoor localization with 5 GHz Wi-Fi

   https://doi.org/10.1109/ICC.2017.7997235  

   Wang, Xuyu ; Wang, Xiangyu ; Mao, Shiwen ( May 2017 , Proc. IEEE ICC 2017)
3. Integration of SDR and UAS for Malicious Wi-Fi Hotspots Detection

   https://doi.org/10.1109/ICNSURV.2019.8735296  

   Wang, Jian ; Juarez, Nicolas ; Kohm, Emma ; Liu, Yongxin ; Yuan, Jiawei ; Song, Houbing ( April 2019 , 2019 IEEE/AIAA Integrated Communications, Navigation and Surveillance Conference (ICNS))
4. Using Channel State Information for Estimating Moisture Content in Woodchips via 5 GHz Wi-Fi

   https://doi.org/10.23919/ACC45564.2020.9147458  

   Suthar, Kerul ; Wang, Jin ; Jiang, Zhihua ; He, Q. Peter ( July 2020 , 2020 American Control Conference (ACC))

   For the pulping process in a pulp & paper plant that uses wood as a raw material, it is important to have real-time knowledge about the moisture content of the woodchips so that the process can be optimized and/or controlled correspondingly to achieve satisfactory product quality while minimizing the consumption of energy and chemicals. Both destructive and non-destructive methods have been developed for estimating moisture content in woodchips, but these methods are often lab-based that cannot be implemented online, or too fragile to stand the harsh manufacturing environment. To address these limitations, we propose a non-destructive and economic approach based on 5 GHz Wi-Fi and use channel state information (CSI) to estimate the moisture content in woodchips. In addition, we propose to use statistics pattern analysis (SPA) to extract features from raw CSI data of amplitude and phase difference. The extracted features are then used for classification model building using linear discriminant analysis (LDA) and subspace discriminant (SD) classification. The woodchip moisture classification results are validated using the oven drying method.
5. LTE Misbehavior Detection in Wi-Fi/LTE Coexistence Under the LAA-LTE Standard

   https://doi.org/10.1145/3212480.3212485  

   Samy, Islam ; Lazos, Loukas ; Xiao, Yong ; Li, Ming ; Krunz, Marwan ( July 2018 , 11th ACM Conference on Security & Privacy in Wireless and Mobile Networks)